The present invention generally relates to methods and systems for managing call event data for calls between callers and agents accomplished though carriers. Methods and systems are also included for data associated with managing broadcast campaigns.
Aggregation of customer activities and sales data is a multi-billion dollar industry. Tracking customer marketing data is important to allow companies to serve their customers more efficiently and provide more focused services.
Examples of marketing data that may be collected relating to customers include, among others, the geographic distribution of customers, the demographic data of customers most likely to buy products and services, and the effectiveness of advertising campaigns. Other types of data that represent significant value for companies, also referred to herein as agents, include individual customer data such as a customer's identity, individual customer demographic information, the number and frequency of previous customer calls, and other past customer activity.
Companies can more effectively target their marketing and sales campaigns upon assessing the effectiveness of current and past advertising campaigns. For example, if a company determines that certain geographic regions or certain customer demographics have a much higher customer response rate to mail-out advertising campaigns, the company may more effectively target the more responsive customers when armed with such aggregated customer information.
Traditional methods of assessing responsiveness to advertising campaigns include labor-intensive efforts such as customer service representatives inquiring as to how customers heard about the company or agent, either through survey cards or verbal interrogation. Conventional methods of collecting and storing customer data and information such as customer identity, number and frequency of calls, prior customer purchases, and other relevant customer history is often collected manually by customer service representatives who input such information into a database. By requiring such data to be inputted manually, the collection of customer data is susceptible to the types of errors associated with manual entry of data and furthermore, such manual entry of data is inefficient and time-consuming.
Another problem present in the customer service and marketing industries is evaluating the effectiveness of telephone marketing campaigns. Customer service representatives often call customers or potential customers from the agent work site from a company-provided list of customer phone numbers. Direct calls to customers are often tracked when calls are made from the company site (i.e. either automatically or by manual input by a customer service representative). Sometimes, customer service representatives will print out lists of customer phone numbers to call when off-site or outside of regular business hours. One problem inherent in calling customers when agents are off-site is that calls to customers are not tracked as they would have be if the customer service representative were on-site. Thus, improved methods for tracking agent calls to customers are needed, including methods of tracking relevant marketing data associated with such agent-to-customer calls.
Another problem faced by marketers is the time lag and inefficiency inherent in conventional methods of viewing and updating customer data when receiving a call from a customer. Conventional methods involve determining the identity of a customer, which is often accomplished through verbal interrogation, and then, manually searching a database of previously-collected customer data. Then, a customer service representative usually manually updates the customer information in the database. Again, such methods are time-consuming and inefficient.
The advent of do-not-call (DNC) lists poses additional problems for marketing companies. Marketers now must verify that a customer is not on a do-not-call list before initiating a call to a customer. Conventional methods for determining whether a customer is on a do-not-call list are accomplished by manually checking a do-not-call list or database. Updating do-not-call lists and databases is also usually accomplished manually. Such manual methods of checking and updating do-not-call lists are inefficient and time-consuming.
Additionally, improved methods of reducing lead time in establishing contact with prospective customers are also needed. For example, customers often indicate an interest in products or services through e-mails or via web-based submissions. Reducing the lead time in contacting these customers increases the likelihood of a completed sale while a customer is still interested in the products and services. Waiting too long to establish contact with a customer increases the likelihood that the customer will lose interest or move on to another source for acquiring the products and services.
Thus, conventional methods of collecting and managing call event data suffer from one or more disadvantages. Other disadvantages will be apparent to one of ordinary skill in the art with the benefit of this disclosure.